Abstract
Recent research shows that most Brazilian students have serious problems regarding their reading skills. The full development of this skill is key for the academic and professional future of every citizen. Tools for classifying the complexity of reading materials for children aim to improve the quality of the model of teaching reading and text comprehension. For English, Feng’s work [11] is considered the state-of-art in grade level prediction and achieved 74 % of accuracy in automatically classifying 4 levels of textual complexity for close school grades. There are no classifiers for nonfiction texts for close grades in Portuguese. In this article, we propose a scheme for manual annotation of texts in 5 grade levels, which will be used for customized reading to avoid the lack of interest by students who are more advanced in reading and the blocking of those that still need to make further progress. We obtained 52 % of accuracy in classifying texts into 5 levels and 74 % in 3 levels. The results prove to be promising when compared to the state-of-art work.
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Notes
- 1.
Available at oecd.org/education/PISA-2012-results-brazil.pdf.
- 2.
Available at primeiro-livro.com.
- 3.
Available at rede.novaescolaclube.org.br.
- 4.
Available at lexile.com.
- 5.
Available at tea.cohmetrix.com.
- 6.
Available at nilc.icmc.usp.br/coh-metrix-port.
- 7.
Available at www.weeklyreader.com.
- 8.
Provinha Brasil is a test to evaluate how much children have learned about Portuguese and Mathematics subjects. Available at provinhabrasil.inep.gov.br.
- 9.
Available at http://www.educacao.sp.gov.br/saresp.
- 10.
Prova Brasil is a test to evaluate the quality of the educational brazilian system. Available at http://portal.mec.gov.br/prova-brasil.
- 11.
Available at nilc.icmc.usp.br/nilc/images/download/corpusNilc.zip.
- 12.
Available at chc.cienciahoje.uol.com.br.
- 13.
Available at www.folha.uol.com.br/folhinha.
- 14.
Available at zh.clicrbs.com.br/rs.
- 15.
Available at mundoestranho.abril.com.br.
- 16.
Available at sites.google.com/site/provassaresp.
- 17.
It was used a libsvm implementation of SVM classifier.
- 18.
Available at http://143.107.183.175:22680.
- 19.
Available at http://143.107.183.175:21380/portlex/index.php/en/liwc.
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Hartmann, N., Cucatto, L., Brants, D., Aluísio, S. (2016). Automatic Classification of the Complexity of Nonfiction Texts in Portuguese for Early School Years. In: Silva, J., Ribeiro, R., Quaresma, P., Adami, A., Branco, A. (eds) Computational Processing of the Portuguese Language. PROPOR 2016. Lecture Notes in Computer Science(), vol 9727. Springer, Cham. https://doi.org/10.1007/978-3-319-41552-9_2
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